Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish
Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus statistics, fragmenting semantically loaded suffixes and -- in the case of WordPiece and rule-based analyzers -- failing to decode their output back to the original text. This paper presents \textbf{Morpheus}, a neural morpheme-boundary model for Turkish that is at once a lossless, morphology-aware tokenizer and a word-embedding producer. A differentiable Poisson-binomial dynamic program turns per-character boundary probabilities into soft morpheme memberships during training and exact segments at inference, with no string normalization, so $\mathrm...
| Authors | Tolga Şakar |
|---|---|
| Primary category | cs.CL |
| Published | 17 June 2026 |
| Last updated at source | 2 October 2026 |
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